Car-pool vehicles and other vehicles carrying multiple passengers reduce fuel consumption, pollution, and highway congestion, relative to single-occupancy vehicles. Highway authorities provide various incentives for high occupancy vehicles which include allowing such vehicles to travel in traffic lanes limited to high occupancy vehicles (HOV lanes) and traffic lanes where a toll charged is reduced or eliminated for high occupancy vehicles (HOT lanes). Monetary penalties are imposed on drivers of vehicles travelling with less than a predetermined number of occupants (e.g., less than 2) in these restricted lanes. Recent efforts have been directed toward sensing and image capture systems and methods to effectuate HOV lane enforcement. Further development in this art is needed as entirely automatic solutions for determining the number of occupants in a moving motor vehicle can be quite challenging. While ordinary visible-light can be used for automated vehicle occupancy detection through the front windshield under ideal conditions, cabin penetration using visible light can be easily compromised by factors such as tinted side windshields as well as environmental conditions such as rain, snow, dirt, and the like. Moreover, artificial visible illumination at night may be distracting to drivers. Near infrared (NIR) illumination's one primary advantage over a visible light illumination source is that NIR illumination is less intrusive to the human eye. Thus, the ability to specifically detect humans improves by working in these wavelength bands. Not only does this make such a system more resistant to efforts to defeat it, but the task of human occupancy detection becomes more achievable and more reliable.
Active near-infrared (NIR) illumination has been applied to address those extrinsic effects but better overall performance is still desired in practical applications due to the similarity in reflectance of human skin and other materials, reflected light from windows, stray light from the environment, weather conditions, etc. Single-band infrared cameras using 2D imaging in the NIR wavelength range with CCD or CMOS detector arrays are available at relatively low cost. Many multi-band infrared camera systems use the short wave infrared (SWIR) band by imaging on, for instance, an InGaAs detector array with multiple filters. These systems exploit physical geometries and material properties at different optical wavelengths in the infrared band. Furthermore, in the SWIR band, human skin has reflectance values below other materials, such as cotton, wool, polyamide, and leather that are commonly found inside a passenger compartment of a motor vehicle. Single-band approaches have been demonstrated to be effective in detecting front-seat passengers. However, comparing to the single-band approach, biometric based, i.e., skin identification, HOV/HOT violation detection is more robust against object occlusion and posture variations. This is especially true for rear-seat passenger detection where only partial faces are likely to be captured in the image data. Rear-seat passenger detection is of particular interest to HOV3 systems where 3 or more vehicle occupants are required and in HOT enforcement where the amount of toll depends on the number of passengers in the vehicle, in both the front and rear seats. There is customer-driven demand for a multi-band IR camera system for HOV/HOT violation detection using a spectral mosaic filter. Methods are needed for processing image data from an image sensor that incorporates a mosaic infrared filter arranged in a pattern for material identification in a vehicle occupancy detection system.
In order to reconstruct the full image from the raw image data, interpolation needs to be performed to fill in the blanks for each spectral components acquired using a mosaic filter. A demosaicing algorithm estimates, for each pixel in the image, intensity levels for all spectral components. For example, most modern digital cameras acquire images using a single image sensor overlaid with a color filter array, so demosaicing is part of the processing pipeline required to render images into a viewable format. The reader is directed to the survey paper: “Image Demosaicing: A Systematic Survey”, by Xin Li, Bahadir Gunturk and Lei Zhang, Proceedings of SPIE, Vol. 6822, Issue No 2, pp. 68221J-68221J-15(2008), ISSN: 0277786X.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods for performing material identification from a patterned image captured using a multi-band infrared camera system with a mosaic of spectral filter cells arrayed in a geometric pattern without having to perform a demosaicing operation such that materials of objects in the patterned image can be identified.